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Machine Learning (ML)
PythonAdvanced degree in computer science, math, statistics or a related discipline ( Must have master degree )
Extensive data modeling and data architecture skills
Programming experience in Python, R
Background in machine learning frameworks such as TensorFlow or Keras
Knowledge of Hadoop or another distributed computing systems
Experience working in an Agile environment
Advanced math skills (Linear algebra
Discrete math
Differential equations (ODEs and numerical)
Theory of statistics 1
Numerical analysis 1 (numerical linear algebra) and 2 (quadrature)
Abstract algebra
Number theory
Real analysis
Complex analysis
Intermediate analysis (point set topology)) ( important )
Strong written and verbal communications
Hands on experience on NLP and NLG
Experience in advanced statistical techniques and concepts. ( GLM/regression, Random forest, boosting, trees, text mining ) and experience with application.
Data ScienceMachine Learning (ML)About UpSolve
We built and deliver complex AI solutions which help drive business decisions faster and more accurately. We are a typical AI company and have a range of solutions developed on Video, Image and Text.
What you will do
- Stay informed on new technologies and implement cautiously
- Maintain necessary documentation for the project
- Fix the issues reported by application users
- Plan, build, and design solutions with a mental note of future requirements
- Coordinate with the development team to manage fixes, code changes, and merging
Location: Mumbai
Working Mode: Remote
What are we looking for
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
- Minimum 2 years of professional experience in software development, with a focus on machine learning and full stack development.
- Strong proficiency in Python programming language and its machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
- Experience in developing and deploying machine learning models in production environments.
- Proficiency in web development technologies including HTML, CSS, JavaScript, and front-end frameworks such as React, Angular, or Vue.js.
- Experience in designing and developing RESTful APIs and backend services using frameworks like Flask or Django.
- Knowledge of databases and SQL for data storage and retrieval.
- Familiarity with version control systems such as Git.
- Strong problem-solving and analytical skills.
- Excellent communication and collaboration abilities.
- Ability to work effectively in a fast-paced and dynamic team environment.
- Good to have Cloud Exposure
Machine Learning (ML)Data Science- Develop, train, and optimize machine learning models using Python, ML algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and other relevant technologies.
- Implement MLOps best practices, including model deployment, monitoring, and versioning.
- Utilize Vertex AI, MLFlow, KubeFlow, TFX, and other relevant MLOps tools and frameworks to streamline the machine learning lifecycle.
- Collaborate with cross-functional teams to design and implement CI/CD pipelines for continuous integration and deployment using tools such as GitHub Actions, TeamCity, and similar platforms.
- Conduct research and stay up-to-date with the latest advancements in machine learning, deep learning, and MLOps technologies.
- Provide guidance and support to data scientists and software engineers on best practices for machine learning development and deployment.
- Assist in developing tooling strategies by evaluating various options, vendors, and product roadmaps to enhance the efficiency and effectiveness of our AI and data science initiatives.
Java- Core Java: advanced level competency, should have worked on projects with core Java development.
- Linux shell : advanced level competency, work experience with Linux shell scripting, knowledge and experience to use important shell commands
- Rdbms, SQL: advanced level competency, Should have expertise in SQL query language syntax, should be well versed with aggregations, joins of SQL query language.
- Data structures and problem solving: should have ability to use appropriate data structure.
- AWS cloud : Good to have experience with aws serverless toolset along with aws infra
- Data Engineering ecosystem : Good to have experience and knowledge of data engineering, ETL, data warehouse (any toolset)
- Hadoop, HDFS, YARN : Should have introduction to internal working of these toolsets
- HIVE, MapReduce, Spark: Good to have experience developing transformations using hive queries, MapReduce job implementation and Spark Job Implementation. Spark implementation in Scala will be plus point.
- Airflow, Oozie, Sqoop, Zookeeper, Kafka: Good to have knowledge about purpose and working of these technology toolsets. Working experience will be a plus point here.
Machine Learning (ML)Data Science1.Advanced knowledge of statistical techniques, NLP, machine learning algorithms and deep
learning
frameworks like Tensorflow, Theano, Keras, Pytorch
2. Proficiency with modern statistical modeling (regression, boosting trees, random forests,
etc.),
machine learning (text mining, neural network, NLP, etc.), optimization (linear
optimization,
nonlinear optimization, stochastic optimization, etc.) methodologies.
3. Build complex predictive models using ML and DL techniques with production quality
code and jointly
own complex data science workflows with the Data Engineering team.
4. Familiar with modern data analytics architecture and data engineering technologies
(SQL and No-SQL databases)
5. Knowledge of REST APIs and Web Services
6. Experience with Python, R, sh/bash
Required Skills (Non-Technical):-
1. Fluent in English Communication (Spoken and verbal)
2. Should be a team player
3. Should have a learning aptitude
4. Detail-oriented, analytical and inquisitive
5. Ability to work independently and with others
6. Extremely organized with strong time-management skills
7. Problem Solving & Critical Thinking
Required Experience Level :- Senior level- 4+Years
Work Location : Pune preferred, Remote option available
Work Timing : 2:30 PM to 11:30 PM IST
About Telstra
Telstra is Australia’s leading telecommunications and technology company, with operations in more than 20 countries, including In India where we’re building a new Innovation and Capability Centre (ICC) in Bangalore.
We’re growing, fast, and for you that means many exciting opportunities to develop your career at Telstra. Join us on this exciting journey, and together, we’ll reimagine the future.
Why Telstra?
- We're an iconic Australian company with a rich heritage that's been built over 100 years. Telstra is Australia's leading Telecommunications and Technology Company. We've been operating internationally for more than 70 years.
- International presence spanning over 20 countries.
- We are one of the 20 largest telecommunications providers globally
- At Telstra, the work is complex and stimulating, but with that comes a great sense of achievement. We are shaping the tomorrow's modes of communication with our innovation driven teams.
Telstra offers an opportunity to make a difference to lives of millions of people by providing the choice of flexibility in work and a rewarding career that you will be proud of!
About the team
Being part of Networks & IT means you'll be part of a team that focuses on extending our network superiority to enable the continued execution of our digital strategy.
With us, you'll be working with world-leading technology and change the way we do IT to ensure business needs drive priorities, accelerating our digitisation programme.
Focus of the role
Any new engineer who comes into data chapter would be mostly into developing reusable data processing and storage frameworks that can be used across data platform.
About you
To be successful in the role, you'll bring skills and experience in:-
Essential
- Hands-on experience in Spark Core, Spark SQL, SQL/Hive/Impala, Git/SVN/Any other VCS and Data warehousing
- Skilled in the Hadoop Ecosystem(HDP/Cloudera/MapR/EMR etc)
- Azure data factory/Airflow/control-M/Luigi
- PL/SQL
- Exposure to NOSQL(Hbase/Cassandra/GraphDB(Neo4J)/MongoDB)
- File formats (Parquet/ORC/AVRO/Delta/Hudi etc.)
- Kafka/Kinesis/Eventhub
Highly Desirable
Experience and knowledgeable on the following:
- Spark Streaming
- Cloud exposure (Azure/AWS/GCP)
- Azure data offerings - ADF, ADLS2, Azure Databricks, Azure Synapse, Eventhubs, CosmosDB etc.
- Presto/Athena
- Azure DevOps
- Jenkins/ Bamboo/Any similar build tools
- Power BI
- Prior experience in building or working in team building reusable frameworks,
- Data modelling.
- Data Architecture and design principles. (Delta/Kappa/Lambda architecture)
- Exposure to CI/CD
- Code Quality - Static and Dynamic code scans
- Agile SDLC
If you've got a passion to innovate, succeed as part of a great team, and looking for the next step in your career, we'd welcome you to apply!
___________________________
We’re committed to building a diverse and inclusive workforce in all its forms. We encourage applicants from diverse gender, cultural and linguistic backgrounds and applicants who may be living with a disability. We also offer flexibility in all our roles, to ensure everyone can participate.
To learn more about how we support our people, including accessibility adjustments we can provide you through the recruitment process, visit tel.st/thrive.
Data ScienceMachine Learning (ML)XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
vision to evolve into a strong full-service logistics organization reflects itself in the various lines of business like B2C
logistics 3PL, B2B Xpress, Hyperlocal and Cross border Logistics.
Our strong domain expertise and constant focus on innovation has helped us rapidly evolve as the most trusted
logistics partner of India. XB has progressively carved our way towards best-in-class technology platforms, an
extensive logistics network reach, and a seamless last mile management system.
While on this aggressive growth path, we seek to become the one-stop-shop for end-to-end logistics solutions. Our
big focus areas for the very near future include strengthening our presence as service providers of choice and
leveraging the power of technology to drive supply chain efficiencies.
Job Overview
XpressBees would enrich and scale its end-to-end logistics solutions at a high pace. This is a great opportunity to join
the team working on forming and delivering the operational strategy behind Artificial Intelligence / Machine Learning
and Data Engineering, leading projects and teams of AI Engineers collaborating with Data Scientists. In your role, you
will build high performance AI/ML solutions using groundbreaking AI/ML and BigData technologies. You will need to
understand business requirements and convert them to a solvable data science problem statement. You will be
involved in end to end AI/ML projects, starting from smaller scale POCs all the way to full scale ML pipelines in
production.
Seasoned AI/ML Engineers would own the implementation and productionzation of cutting-edge AI driven algorithmic
components for search, recommendation and insights to improve the efficiencies of the logistics supply chain and
serve the customer better.
You will apply innovative ML tools and concepts to deliver value to our teams and customers and make an impact to
the organization while solving challenging problems in the areas of AI, ML , Data Analytics and Computer Science.
Opportunities for application:
- Route Optimization
- Address / Geo-Coding Engine
- Anomaly detection, Computer Vision (e.g. loading / unloading)
- Fraud Detection (fake delivery attempts)
- Promise Recommendation Engine etc.
- Customer & Tech support solutions, e.g. chat bots.
- Breach detection / prediction
An Artificial Intelligence Engineer would apply himself/herself in the areas of -
- Deep Learning, NLP, Reinforcement Learning
- Machine Learning - Logistic Regression, Decision Trees, Random Forests, XGBoost, etc..
- Driving Optimization via LPs, MILPs, Stochastic Programs, and MDPs
- Operations Research, Supply Chain Optimization, and Data Analytics/Visualization
- Computer Vision and OCR technologies
The AI Engineering team enables internal teams to add AI capabilities to their Apps and Workflows easily via APIs
without needing to build AI expertise in each team – Decision Support, NLP, Computer Vision, for Public Clouds and
Enterprise in NLU, Vision and Conversational AI.Candidate is adept at working with large data sets to find
opportunities for product and process optimization and using models to test the effectiveness of different courses of
action. They must have knowledge using a variety of data mining/data analysis methods, using a variety of data tools,
building, and implementing models, using/creating algorithms, and creating/running simulations. They must be
comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Roles & Responsibilities
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection,
Risk prevention, Predictive analytics), computer vision, natural language processing (NLP) and speech that
work out of the box.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Build core of Artificial Intelligence and AI Services such as Decision Support, Vision, Speech, Text, NLP, NLU,
and others.
● Leverage Cloud technology –AWS, GCP, Azure
● Experiment with ML models in Python using machine learning libraries (Pytorch, Tensorflow), Big Data,
Hadoop, HBase, Spark, etc
● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to
drive business solutions.
● Mine and analyze data from company databases to drive optimization and improvement of product
development, marketing techniques and business strategies.
● Assess the effectiveness and accuracy of new data sources and data gathering techniques.
● Develop custom data models and algorithms to apply to data sets.
● Use predictive modeling to increase and optimize customer experiences, supply chain metric and other
business outcomes.
● Develop company A/B testing framework and test model quality.
● Coordinate with different functional teams to implement models and monitor outcomes.
● Develop processes and tools to monitor and analyze model performance and data accuracy.
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Deliver machine learning and data science projects with data science techniques and associated libraries
such as AI/ ML or equivalent NLP (Natural Language Processing) packages. Such techniques include a good
to phenomenal understanding of statistical models, probabilistic algorithms, classification, clustering, deep
learning or related approaches as it applies to financial applications.
● The role will encourage you to learn a wide array of capabilities, toolsets and architectural patterns for
successful delivery.
What is required of you?
You will get an opportunity to build and operate a suite of massive scale, integrated data/ML platforms in a broadly
distributed, multi-tenant cloud environment.
● B.S., M.S., or Ph.D. in Computer Science, Computer Engineering
● Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.
● Experience with building high-performance, resilient, scalable, and well-engineered systems
● Experience in CI/CD and development best practices, instrumentation, logging systems
● Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights
from large data sets.
● Experience working with and creating data architectures.
● Good understanding of various machine learning and natural language processing technologies, such as
classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.
● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest,
Boosting, Trees, text mining, social network analysis, etc.
● Knowledge on using web services: Redshift, S3, Spark, Digital Ocean, etc.
● Knowledge on creating and using advanced machine learning algorithms and statistics: regression,
simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
● Knowledge on analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics,
AdWords, Crimson Hexagon, Facebook Insights, etc.
● Knowledge on distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, Kafka etc.
● Knowledge on visualizing/presenting data for stakeholders using: Quicksight, Periscope, Business Objects,
D3, ggplot, Tableau etc.
● Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
● Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests, and proper usage, etc.) and experience with applications.
● Experience building data pipelines that prep data for Machine learning and complete feedback loops.
● Knowledge of Machine Learning lifecycle and experience working with data scientists
● Experience with Relational databases and NoSQL databases
● Experience with workflow scheduling / orchestration such as Airflow or Oozie
● Working knowledge of current techniques and approaches in machine learning and statistical or
mathematical models
● Strong Data Engineering & ETL skills to build scalable data pipelines. Exposure to data streaming stack (e.g.
Kafka)
● Relevant experience in fine tuning and optimizing ML (especially Deep Learning) models to bring down
serving latency.
● Exposure to ML model productionzation stack (e.g. MLFlow, Docker)
● Excellent exploratory data analysis skills to slice & dice data at scale using SQL in Redshift/BigQuery.
JOB DESCRIPTION:. THE IDEAL CANDIDATE WILL:
• Ensure new features and subject areas are modelled to integrate with existing structures and provide a consistent view. Develop and maintain documentation of the data architecture, data flow and data models of the data warehouse appropriate for various audiences. Provide direction on adoption of Cloud technologies (Snowflake) and industry best practices in the field of data warehouse architecture and modelling.
• Providing technical leadership to large enterprise scale projects. You will also be responsible for preparing estimates and defining technical solutions to proposals (RFPs). This role requires a broad range of skills and the ability to step into different roles depending on the size and scope of the project Roles & Responsibilities.
ELIGIBILITY CRITERIA: Desired Experience/Skills:
• Must have total 5+ yrs. in IT and 2+ years' experience working as a snowflake Data Architect and 4+ years in Data warehouse, ETL, BI projects.
• Must have experience at least two end to end implementation of Snowflake cloud data warehouse and 3 end to end data warehouse implementations on-premise preferably on Oracle.
• Expertise in Snowflake – data modelling, ELT using Snowflake SQL, implementing complex stored Procedures and standard DWH and ETL concepts
• Expertise in Snowflake advanced concepts like setting up resource monitors, RBAC controls, virtual warehouse sizing, query performance tuning, Zero copy clone, time travel and understand how to use these features
• Expertise in deploying Snowflake features such as data sharing, events and lake-house patterns
• Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, Big Data model techniques using Python
• Experience in Data Migration from RDBMS to Snowflake cloud data warehouse
• Deep understanding of relational as well as NoSQL data stores, methods and approaches (star and snowflake, dimensional modelling)
• Experience with data security and data access controls and design
• Experience with AWS or Azure data storage and management technologies such as S3 and ADLS
• Build processes supporting data transformation, data structures, metadata, dependency and workload management
• Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning and troubleshoot
• Provide resolution to an extensive range of complicated data pipeline related problems, proactively and as issues surface
• Must have expertise in AWS or Azure Platform as a Service (PAAS)
• Certified Snowflake cloud data warehouse Architect (Desirable)
• Should be able to troubleshoot problems across infrastructure, platform and application domains.
• Must have experience of Agile development methodologies
• Strong written communication skills. Is effective and persuasive in both written and oral communication
Nice to have Skills/Qualifications:Bachelor's and/or master’s degree in computer science or equivalent experience.
• Strong communication, analytical and problem-solving skills with a high attention to detail.
About you:
• You are self-motivated, collaborative, eager to learn, and hands on
• You love trying out new apps, and find yourself coming up with ideas to improve them
• You stay ahead with all the latest trends and technologies
• You are particular about following industry best practices and have high standards regarding quality
Job Description:
- Working knowledge and hands-on experience of Big Data / Hadoop tools and technologies.
- Experience of working in Pig, Hive, Flume, Sqoop, Kafka etc.
- Database development experience with a solid understanding of core database concepts, relational database design, ODS & DWH.
- Expert level knowledge of SQL and scripting preferably UNIX shell scripting, Perl scripting.
- Working knowledge of Data integration solution and well-versed with any ETL tool (Informatica / Datastage / Abinitio/Pentaho etc).
- Strong problem solving and logical reasoning ability.
- Excellent understanding of all aspects of the Software Development Lifecycle.
- Excellent written and verbal communication skills.
- Experience in Java will be an added advantage
- Knowledge of object oriented programming concepts
- Exposure to ISMS policies and procedures.
Data ScienceMachine Learning (ML)Python
Deep Learning- 3+ years of experience in Machine Learning
- Bachelors/Masters in Computer Engineering/Science.
- Bachelors/Masters in Engineering/Mathematics/Statistics with sound knowledge of programming and computer concepts.
- 10 and 12th acedemics 70 % & above.
Skills :
- Strong Python/ programming skills
- Good conceptual understanding of Machine Learning/Deep Learning/Natural Language Processing
- Strong verbal and written communication skills.
- Should be able to manage team, meet project deadlines and interface with clients.
- Should be able to work across different domains and quickly ramp up the business processes & flows & translate business problems into the data solutions
Machine Learning (ML)PythonDeep LearningJob Description:
Roles & Responsibilities:
· You will be involved in every part of the project lifecycle, right from identifying the business problem and proposing a solution, to data collection, cleaning, and preprocessing, to training and optimizing ML/DL models and deploying them to production.
· You will often be required to design and execute proof-of-concept projects that can demonstrate business value and build confidence with CloudMoyo’s clients.
· You will be involved in designing and delivering data visualizations that utilize the ML models to generate insights and intuitively deliver business value to CXOs.
Desired Skill Set:
· Candidates should have strong Python coding skills and be comfortable working with various ML/DL frameworks and libraries.
· Hands-on skills and industry experience in one or more of the following areas is necessary:
1) Deep Learning (CNNs/RNNs, Reinforcement Learning, VAEs/GANs)
2) Machine Learning (Regression, Random Forests, SVMs, K-means, ensemble methods)
3) Natural Language Processing
4) Graph Databases (Neo4j, Apache Giraph)
5) Azure Bot Service
6) Azure ML Studio / Azure Cognitive Services
7) Log Analytics with NLP/ML/DL
· Previous experience with data visualization, C# or Azure Cloud platform and services will be a plus.
· Candidates should have excellent communication skills and be highly technical, with the ability to discuss ideas at any level from executive to developer.
· Creative problem-solving, unconventional approaches and a hacker mindset is highly desired.
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